Permanent-magnet synchronous motor (PMSM) is a nonlinear, multivariate, strongly coupled system with uncertain external interference. A general control method cannot meet system requirements. This study proposes an optimal control strategy based on active disturbance rejection control (ADRC) to achieve high-precision control of PMSM. First, interpolation fitting is used to construct a nonlinear function with improved continuity and derivative near the origin and segment points. Second, various components of active disturbance rejection control are constructed based on the new nonlinear function, which mainly improves the extended state observer and nonlinear state error feedback. Simulation results show that under similar parameters, the improved active disturbance rejection control has smaller overshoot, faster tracking capacity, and stronger anti-interference capability compared with traditional active disturbance rejection control. Finally, the optimized active disturbance rejection control is used in the motion control system of PMSM. Experimental results show that the proposed optimal control strategy is simple and has good control performance.

This study proposes a method based on Dempster-Shafer theory (DST) and fuzzy neural network (FNN) to improve the reliability of recognizing fatigue driving. This method measures driving states using multifeature fusion. First, FNN is introduced to obtain the basic probability assignment (BPA) of each piece of evidence given the lack of a general solution to the definition of BPA function. Second, a modified algorithm that revises conflict evidence is proposed to reduce unreasonable fusion results when unreliable information exists. Finally, the recognition result is given according to the combination of revised evidence based on Dempster’s rule. Experiment results demonstrate that the recognition method proposed in this paper can obtain reasonable results with the combination of information given by multiple features. The proposed method can also effectively and accurately describe driving states.

An improved extended state observer is designed to eliminate the influences of speed control for a permanent magnet synchronous motor. The improved extended state observer is designed based on a new nonlinear function. This function exhibits better continuity and derivability than previously available functions and can effectively reduce the highfrequency flutter phenomenon. The nonlinear dynamics, model uncertainty, and external disturbances of the permanent magnet synchronous motor speed control system are extended to a new state. The improved extended state observer is utilized to observe this state. The overtime variation of the permanent magnet synchronous motor speed control system can be predicted and compensated in real time by the improved extended state observer. Therefore, the improved extended state observer, which is designed based on the new nonlinear function, can eliminate the disturbances on the permanent magnet synchronous motor speed control system. Finally, simulation experiments are performed and results show that the permanent magnet synchronous motor speed control system with improved extended state observer exhibits better performances.